• Journal of international Conference on Electrical Machines and Systems
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• 제2권3호
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• pp.330-335
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• 2013

This paper performs two kinds of Field-Oriented Control (FOC) for dual three phase permanent magnet synchronous motor (DTP-PMSM).The first is based on vector space decomposition to study the effect of current harmonics on electromechanical energy conversion. And the second presents the coupling relations between two sets of windings using two d-q transformation. And then this paper has deeply studied the differences between these two strategies, the different effect on the control of harmonic current and the reason for these differences. MATLAB-based Simulation studies of a 3KW DTP-PMSM are carried out to verify the analysis of differences between the two FOC strategies.

• 산경연구논집
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• 제11권3호
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• pp.7-17
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• 2020

Purpose: This study reexamines the test on the pricing of accruals quality. Theory suggests that information risk is a priced risk factor. Using accruals quality as the proxy for information risk, researchers have tested the pricing of information risk. The results are inconsistent potentially because of the information shock in the realized returns that are used as the proxy for expected returns. Based on this argument, this study revisits this issue excluding information-shock-free measure of expected returns. Research design, data and methodology: This study estimates expected returns using the vector autoregression model. This method extracts information shocks more thoroughly than the methods in prior studies; therefore, the concern regarding information shock is minimized. As risk premiums are larger in recession periods than in expansion periods, recession and expansion subsamples were used to confirm the robustness of the main findings. For the pricing test, this study uses two-stage cross-sectional regression. Results: Empirical results find evidence that accruals quality is a priced risk factor. Furthermore, this study finds that the pricing of accruals quality is observed only in recession periods. Conclusions: This study supports the argument that accruals quality, as well as the pricing of information risk, is a priced risk factor.

• Journal of Communications and Networks
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• 제17권5호
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• pp.491-498
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• 2015

Recognition of radar emitter signals is one of core elements in radar reconnaissance systems. A novel method based on singular value decomposition (SVD) and the main ridge slice of ambiguity function (AF) is presented for attaining a higher correct recognition rate of radar emitter signals in case of low signal-to-noise ratio. This method calculates the AF of the sorted signal and ascertains the main ridge slice envelope. To improve the recognition performance, SVD is employed to eliminate the influence of noise on the main ridge slice envelope. The rotation angle and symmetric Holder coefficients of the main ridge slice envelope are extracted as the elements of the feature vector. And kernel fuzzy c-means clustering is adopted to analyze the feature vector and classify different types of radar signals. Simulation results indicate that the feature vector extracted by the proposed method has satisfactory aggregation within class, separability between classes, and stability. Compared to existing methods, the proposed feature recognition method can achieve a higher correct recognition rate.

• Journal of Power Electronics
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• 제16권3호
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• pp.936-945
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• 2016

Large magnitude common-mode voltage (CMV) and its variation dv/dt have an adverse effect on motor drives that leads to early winding failure and bearing deterioration. For matrix converters, the switch states that connect each output line to a different input phase result in the lowest CMV among all of the valid switch states. To reduce the output CMV for matrix converters, this paper presents a new space vector modulation (SVM) strategy by utilizing these switch states. By this mean, the peak value and the root mean square of the CMV are dramatically decreased. In comparison with the conventional SVM methods this strategy has a similar computation overhead. Experiment results are shown to validate the effectiveness of the proposed modulation method.

• 한국산업정보학회논문지
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• 제15권2호
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• pp.49-57
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• 2010

본 논문에서는 역전파 신경망 알고리즘(BPNN: Back Propagation Neural Network)과 Singular Value Decomposition(SVD)를 이용하는 한글 문서 분류 시스템을 제안한다. BPNN은 학습을 통하여 만들어진 네트워크를 이용하여 문서분류를 수행한다. 이 방법의 어려움은 분류기에 입력되는 특징 공간이 너무 크다는 것이다. SVD를 이용하면 고차원의 벡터를 저차원으로 줄일 수 있고, 또한 의미있는 벡터 공간을 만들어 단어 사이의 중요한 관계성을 구축할 수 있다. 본 논문에서 제안한 BPNN의 성능 평가를 위하여 한국일보-2000/한국일보-40075 문서범주화 실험문서집합의 데이터 셋을 이용하였다. 실험결과를 통하여 BPNN과 SVD를 사용한 시스템이 한글 문서 분류에 탁월한 성능을 가지는 것을 보여준다.

• 한국지능시스템학회논문지
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• 제6권3호
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• pp.3-13
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• 1996

In orde to reduce huge memory requirements of multidimensional CMAC problems, building a CMAC system by problem decomposition is investigated. Decomposition is based on resolving a displacement vector in cartesian coordinates into unit vectors that define a few lower-dimensional CMACs in the CMAC system. A CMAC system for an an in verse kinematics problem for a planar manipulator was simulated and the performance of the system was evaluated in terms of training and output quality.

• 충청수학회지
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• 제7권1호
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• pp.33-39
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• 1994

The purpose of this paper prove the following property; Suppose A has many units (local global ring) and |A/m| > 5 for every maximal ideal $m{\subseteq}A$. Let(E, q) ${\in}$ Q(A) and $E=E_1{\bot}{\cdots}{\bot}E_t$ be an orthogonl decomposition of E with $t{\geq}2$ and $rk(E_i){\geq}1$, for $i=1,{\cdots},t$. Let $x{\in}E$ be a primitive vector. Then there exists ${\sigma}{\in}O(q)$ such that ${\sigma}(x)$ is transversal to this decomposition.

• Korean Journal of Mathematics
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• 제30권1호
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• pp.61-66
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• 2022

A new type of Riemannian manifold called semirecurrent manifold has been defined and some of its geometric properties are studied. Among others we show that the scalar curvature of semirecurrent manifold is constant and hence semirecurrent manifold is also concircularly recurrent. In addition, we show that the associated 1-form (resp. the associated vector field) of semirecurrent manifold is closed (resp. an eigenvector of its Ricci tensor). Furthermore, we prove that if a Riemannian product manifold is semirecurrent, then either one decomposition manifold is locally symmetric or the other decomposition manifold is a space of constant curvature.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 추계학술대회
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• pp.123-123
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• 2003

More elaborated methods allowing the usage of binary classifiers for the resolution of multi-class classification problems are briefly presented. This way of using FSVC to learn a K-class classification problem consists in choosing the maximum applied to the outputs of K FSVC solving a one-per-class decomposition of the general problem.

• 대한원격탐사학회지
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• 제23권2호
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• pp.89-101
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• 2007

이 논문에서는 토지 피복분류를 목적으로 C 밴드와 L 밴드 다중 편광 자료의 결정 수준 융합을 수행하여 융합 효과를 살펴보았다. 앞으로 이용이 가능해질 C 밴드 Radarsat-2 자료와 L 밴드 ALOS PALSAR 자료를 모사하기 위해 C 밴드와 L 밴드 NASA JPL AIRSAR 자료를 감독분류에 이용하였다. Target decomposition으로부터 얻어지는 산란 특성과 관련된 특징들을 입력으로 SVM을 분류 기법으로 적용한 후에, 사후확률을 확률비 모델의 틀안에서 융합하는 결정수준 융합을 수행하였다. 적용 결과, L 밴드가 C 밴드에 비해 피복 구분에 적절한 투과 심도를 나타내어 22% 정도 높은 분류 정확도를 나타내었지만, 결정수준 융합을 통해 개별 토지피복 항목의 구분력의 향상으로 인해 L 밴드 자료의 분류결과에 비해 10% 정도의 보다 향상된 분류 정확도를 얻을 수 있었다.